Calibration Layer
A calibration layer is a post-prediction adjustment appended to a trained machine learning model that rescales its raw output scores or predicted probabilities so they better reflect the true likelihood of…
Model Evaluation
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Generalization
Generalization in machine learning is the ability of a trained model to perform accurately on new, unseen data drawn from the same distribution as its training set
Loss Curve
A loss curve is a plot that shows the value of a loss function over the course of training a machine learning model.
Overfitting
Overfitting is a failure of generalization: a fitted model or a model-selection procedure performs better on the observations used to develop it than on new observations from the population of interest.